We use similar tools for managing cancer and repairing cybersecurity vulnerabilities. Our models of evolutionary biology and ecology are predicting which tumors are likely to become dangerous and how best to manage them. We use immunological concepts to invent new cybersecurity solutions, and we use evolutionary methods to solve software engineering problems. We also use computing and mathematical abstractions to inform biological research, focusing on new approaches to understanding and managing cancer.
Our studies make a difference in
- Using evolutionary computation tools to automatically improve software by fixing bugs, enhancing security and reducing energy costs.
- Applying graph algorithms from computer science to predict genomic diversity.
- Using techniques from agricultural pest management and computational genomics to understand cancer across the tree of life and to prevent human deaths from the evolution of therapeutic resistance in cancers.
- Applying our open source software to screen patients algorithmically for immunotherapy in lieu of expensive wet-lab analysis.
The impact of our research can also be seen in cancer through
- Applying tools from evolutionary biology and ecology to predict which tumors are likely to become dangerous and how best to manage them.
- Developing and running computational simulations of tumors to identify the most promising approaches to cancer prevention and cancer therapy.
- Developing new approaches to cancer prevention based on our studies of how large, long-lived animals have evolved to prevent cancer.
Using the complexities of biology as our guide we provide
- Computational modeling, both agent-based and mathematical, with specialties in immunology and evolution.
- Complex adaptive systems: fundamental science, tools and applications.
- Emergent computation and collective behavior.
- Programmable matter.
- Cybersecurity, cyberpolicy and internet censorship.
- Evolution of cancer.
For more information about our specific studies, please see our faculty publications.